associations between the cyp17, cypib1, comt and shbg polymorphisms and serum sex hormones in...

Associations between the CYP17, CYPIB1, COMT and SHBGpolymorphisms and serum sex hormones in postmenopausalbreast cancer survivors

Page E. Abrahamson1,2, Shelley S. Tworoger3, Erin J. Aiello4, Leslie Bernstein5, CorneliaM. Ulrich1,2, Frank D. Gilliland5, Frank Z. Stanczyk6, Richard Baumgartner7, KathyBaumgartner7, Bess Sorensen1,2, Rachel Ballard-Barbash8, and Anne McTiernan1,21The Fred Hutchinson Cancer Center, Cancer Prevention Program, Seattle, Washington2University of Washington, School of Public Health and Community Medicine, Department ofEpidemiology, Seattle, Washington3Channing Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA4Group Health Center for Health Studies, Seattle, Washington5Department of Preventive Medicine, Keck School of Medicine, University of Southern California,Los Angeles, California6Department of Obstetrics and Gynecology, Keck School of Medicine, University of SouthernCalifornia, Los Angeles, California7Department of Epidemiology and Clinical Investigation Science, University of Louisville,Louisville, KY8Applied Research Program, Division of Cancer Control and Population Sciences, NationalCancer Institute, Bethesda, Maryland, USA

AbstractSeveral polymorphisms have been identified in genes that code for enzymes involved withestrogen biosynthesis and metabolism. Little is known about the functional relevance of thesepolymorphisms on sex hormones in vivo. We examined the association between CYP17, CYP1B1,COMT or SHBG genotypes and serum concentrations of estrone, estradiol, free estradiol, sexhormone binding globulin (SHBG), testosterone, free testosterone and dehyroepiandrosterone in366 post-menopausal breast cancer survivors in New Mexico, California and Washington.Hormone levels were determined by high performance liquid chromatography andradioimmunoassay in blood drawn approximately 2 years post-diagnosis. We used generalizedlinear regression to calculate mean hormone levels by genotype, adjusting for age, race/ethnicity,stage, study site, tamoxifen use, number of remaining ovaries, hormone therapy use, marital statusand BMI. No associations were observed between any of the genotypes and sex hormones whenanalyzing the main effects. In subgroup analyses, androgen levels of Hispanic women with thevariant (A2) CYP17 genotype were 46–87% higher than those of women with the wildtype;androgen levels were 13–20% lower in non-Hispanic whites with the variant genotype; nodifference by genotype was observed for African-American women. Current tamoxifen users withthe variant asn327 SHBG genotype had 81% higher serum SHBG and 39% lower free testosteroneconcentrations than women with the wildtype genotype. Non-tamoxifen users with the variant

DIRECT CORRESPONDENCE TO: Anne McTiernan, MD, PhD, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N,M4-B402, Seattle, WA 98109-1024, Phone: (206) 667-7979, Fax: (206) 667-7850, [email protected].

NIH Public AccessAuthor ManuscriptBreast Cancer Res Treat. Author manuscript; available in PMC 2010 December 6.

Published in final edited form as:Breast Cancer Res Treat. 2007 September ; 105(1): 45–54. doi:10.1007/s10549-006-9426-2.

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SHBG allele had elevated free estradiol levels. These results provide little evidence that theCYP17, CYP1B1, and COMT polymorphisms are associated with different sex hormone levels inpost-menopausal breast cancer survivors.

Keywordsbreast cancer; COMT; CYP17; CYP1B1; estrogen; SHBG; testosterone

IntroductionCumulative exposure to estrogen is thought to be an important risk factor in thedevelopment of breast cancer in women. Estrogenic compounds can lead to increased cellproliferation and possibly act as DNA damaging agents [1–4]. Elevated serum estrogenconcentration is a risk predictor for postmenopausal breast cancer [5]. In addition toinfluencing disease risk, estrogen-related factors may also impact progression as evidencedby the anti-estrogenic role of the selective estrogen-receptor modulator, tamoxifen, inimproving disease prognosis among patients with estrogen receptor (ER)-positive tumors[6]. Many studies have reported poorer survival for factors related to high estrogen levelssuch as obesity [7].

Recent evidence suggests that oxidative metabolites of estrogen, particularly catecholestrogens [3], can form reactive quinones. These compounds may cause DNA adducts andare capable of redox cycling, which generates other reactive oxidative compounds [4]. Thus,understanding the genetic and environmental factors influencing estrogen biosynthesis andsubsequent metabolism is important in understanding breast cancer etiology.

Several single nucleotide polymorphisms (SNPs) have been identified in genes that code forenzymes involved with estrogen biosynthesis (CYP17), metabolism (CYP1B1 and COMT),and bioavailability (SHBG). The CYP17 gene codes for the cytochrome p450C17α enzyme,a 17α-hydroxylase that catalyzes the conversion of pregnenolone and progesterone to 17-OH-Pregnenolone and 17-OH-progesterone, respectively [8]. It also has a 17,20-lyaseactivity that converts the hydroxylase products to dehydroepiandrosterone (DHEAS) andandrostenedione, respectively, which can be further converted to estrogens and testosterone[8]. A variant identified in the 5’ untranslated region is predicted to enhance enzyme activity[9].

CYP1B1 and COMT are involved in metabolizing estrogenic compounds. CYP1B1 is foundat high levels in breast tissue and catalyzes the C4 hydroxylation of estradiol [10]. Theresultant 4-OH catechol estrogen is potentially carcinogenic [11]. The m1 allele, a leucine tovaline substitution at codon 432 (Leu432Val), is common in Caucasians and African-Americans, and may have a higher catalytic activity than the wildtype allele [12,13]. TheCOMT gene encodes catechol-O-methyl-transferase, which converts catechol estrogens intoinactive metabolites [11]. Approximately 25% of Caucasians are homozygous for a valine tomethionine substitution (Val158Met) that causes the enzyme to be 4 to 5 fold less effective atmethylating catechol substrates in vitro [14].

The sex hormone binding globulin (SHBG) gene encodes for a plasma glycoprotein with ahigh binding affinity for estradiol and testosterone [15]. A variant in the gene with anaspartic acid to asparagine substitution at codon 327 (Asp327Asn) creates an additional sitefor N-linked glycosylation [16,17] which may increase circulating SHBG levels and reducecirculating bioavailable estradiol levels by increasing the amount bound to SHBG [18].

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Breast Cancer Res Treat. Author manuscript; available in PMC 2010 December 6.

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Although several studies have explored the relationship between these polymorphisms andsex hormone levels in healthy women [18,19], little is known about these associations inbreast cancer patients. Therefore, this study examined the associations between geneticpolymorphisms in the CYP17, COMT, CYP1B1, and SHBG genes with serum levels of totalestrone, total estradiol, free estradiol, and estrogen precursor hormones in a cohort of post-menopausal breast cancer patients enrolled in the Health, Eating, Activity and Lifestyle(HEAL) study.

MethodsStudy Subjects and Recruitment

The HEAL study is a population-based, multi-center, multi-ethnic prospective cohort studyof 1183 breast cancer survivors who are being followed to determine whether weight,physical activity, diet, sex hormones, other exposures and genetic susceptibilitypolymorphisms affect breast cancer prognosis. Women were recruited into the HEAL studythrough Surveillance, Epidemiology, End Results (SEER) registries in New Mexico, LosAngeles County (CA), and Western Washington. Details of the aims, study design, andrecruitment procedures have been published previously [20].

Briefly, in New Mexico, we recruited 615 women, aged 18 years or older, diagnosed with insitu to Stage IIIA breast cancer between July 1996 and March 1999, and living in Bernalillo,Sante Fe, Sandoval, Valencia, or Taos Counties. In Western Washington, we recruited 202women, between the ages of 40 and 64 years, diagnosed with in situ to Stage IIIA breastcancer between September 1997 and September 1998, and living in King, Pierce, orSnohomish Counties. In Los Angeles County, we recruited 366 African-American womenaged 35–64 with stage 0 to IIIA primary breast cancer diagnosed between May 1995 andMay 1998, who had participated in the Los Angeles portion of the Women’s Contraceptiveand Reproductive Experiences (CARE) Study [21], a case-control study of invasive breastcancer, or who had participated in a parallel case-control study of in situ breast cancer [22].

Participants completed in-person interviews at baseline (within their first year afterdiagnosis; on average 7.5 months post diagnosis) and at 24-months after the baseline visit(within their third year after diagnosis; on average 31.5 months post diagnosis).Standardized questionnaires collected information on health and medication history,reproductive history, family history of breast and other specific cancers, smoking status,history of oral contraceptive and hormone replacement therapy use, selected demographicdata. Post-menopausal status was determined at the 24-month follow-up interview and wasdefined as having either natural menopause with no periods for at least year or surgicalmenopause with bilateral oophorectomy.

Of the 1183 women who completed the baseline interview, a total of 240 women did notreturn for a follow-up visit within three years after diagnosis. Reasons for non-participationwere death (44), too ill (2), refusal (104), spouse would not permit contact (1), moved fromthe study area (16), unable to contact (17), or unable to locate (55).

For the present analysis, we excluded women who did not complete the 24-month interview(240); developed recurrent or new cancer following baseline (84); were pre-menopausal(163),; were taking hormone therapy (other than tamoxifen) at the time of blood draw (35);were missing stage (1), genotyping (93) or hormone (41) data; or were of a race other thanwhite, Hispanic, or African-American (12). An additional 45 women were excluded forunknown menopausal status or hormone levels inconsistent with being post-menopausal. Wefurther excluded another 105 subjects who were not aged 40–64 at baseline in order to use aconsistent age range for each study site; hormone levels for women outside this age limit

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were different compared to the women within the study age range. The study reported hereis based on the remaining 366 postmenopausal women.

Written informed consent was obtained from each subject. We obtained Institutional ReviewBoard approval at each participating center, in accord with an assurance filed with andapproved by the U.S. Department of Health and Human Services.

Hormone AssaysA 30-mL 12-hour fasting blood sample was collected for all patients at the 24-month follow-up interview. Blood was processed within 3 hours of collection; serum was stored in 1.8-mlaliquot tubes at −70 to −80 C.

For Californian participants, all hormone assays except testosterone were performed at theReproductive and Endocrine Research Laboratory at the University of Southern California.Testosterone assays were performed in the Aging and Genetic Epidemiology (AGE)Program Laboratory at the University of New Mexico. For the other two sites (Washingtonand New Mexico), estrone and estradiol were assayed at Quest Diagnostics (San JuanCapistrano, CA) and SHBG, testosterone and DHEAS assays were conducted in the AGElaboratory. All samples were randomly assigned to assay batches and were randomlyordered within each batch. Laboratory personnel performing the assays were blinded topatient identity and personal characteristics.

Estrone and estradiol assay methods consisted of organic solvent extraction, followed bycelite column partition chromatography before quantification by radioimmunoassay (RIA)with sensitivities of 10 and 2 pg/mL, respectively. Testosterone was determined using a RIAkit (Diagnostic Products Corp, Los Angeles, CA) with a sensitivity of sensitivity of 40 pg/mL. SHBG levels were measured with the Radim RIA quantitation SHBG Kit (sensitivity of6 nmol/L; Wien Laboratories, Succasunna, NJ). DHEAS concentrations were determinedusing a DHEAS RIA kit (sensitivity of 1.1 µg/dL; Diagnostic Products Corp).

Intra-assay variability was assessed in a reduced randomly selected sample for all hormones.The coefficients of variation (CV) were calculated to test the assay variability. The CV wasestimated by the standard deviation of the difference of replicated measures divided by themean of the two measures. For California samples, 24 blinded blood samples were randomlyselected for hormone assay repeats. The intra-assay CVs for estrone, estradiol, and SHBGwere 26.2%, 15.4% and 9.3%, respectively. For New Mexico and Washington samples,assays were done in batches, and duplicate aliquots of ten randomly selected participantsamples were assayed per bath. The intra-assay CVs for estrone, estradiol, SHBG, andDHEAS were 29.1%, 28.8% 3.8% and 4.6%, respectively. The intra-assay CV fortestosterone was 12.0% (done for all centers at the AGE laboratory). These CVs areconsistent to those observed in other studies using similar methods for serum concentrationof sex hormones [23,24].

Genotype AssessmentFor the Washington and California subjects, DNA was extracted from buffy coat fractionsusing Phenol/Chloroform methods [25]. The CYP17, CYP1B1, COMT, and SHBGgenotyping were performed at Albany Molecular Research in Bothell, Washington, usingthe Taqman allelic discrimination method with the ABI 7700 Sequence Detection System(Applied Biosystems, Foster City, CA), which has been described [26,27]. Briefly, theassays measure fluorescent intensity released from allele-specific fluorogenic probesfollowing specific PCR amplification of the genomic flanking regions of the SNP of interest.Probes (see Table 1) were 3'-labeled with the TAMRA quencher dye, and wildtype andvariant probes were 5'-labeled with 6-FAM and VIC reporter dyes, respectively (Integrated

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DNA Technologies, Coralville, IA). CYP17 and CYP1B1 probes were complementary totheir corresponding sense strands, whereas the COMT probes were complementary to theantisense strand. We included 10% replica samples and genotype concordance was 100%.

For New Mexico subjects, DNA was isolated from buffy coats using the Puregene DNAisolation kit from Gentra Systems (Minneapolis, MN) at the Protein Chemistry Laboratory atthe UNM Health Science Center (Albuquerque, NM). The CYP17 T/C SNP was assessedusing a PCR/MspA-I restriction enzyme procedure established by Feigelson et al. [9], using5’-cattcgcacctctggagtc-3’ and 5’-ggctcttggggtacttg-3’ primers. CYP1B1 was analyzed usinga PCR/Eco 571 restriction enzyme procedure established by Bailey et al. [10], using primers5’-gtggtttttgtcaaccagtgg-3’ and 5’gcctcttgcttcttattggca-3’. COMT genotype was determinedusing a PCR/Nla-III restriction enzyme procedure [28] using the primers 5’-tactgtggctactcagctgtgc-3’ and 5’-gtgaacgtggtgtgaacacc-3’. We conducted a round-robin tocheck genotyping methods across sites. All round-robin samples were tested at anindependent lab and genotype concordance was 100%. Genotyping was not performed forthe SHBG gene among subjects from New Mexico. Because only 2 Hispanic women hadSHBG genotyping at the other two sites, these values were excluded from the SHBGanalyses.

Statistical AnalysisFree (non-SHBG bound) estradiol and testosterone were calculated indirectly from totalestradiol or testosterone, respectively, and serum SHBG using a mathematical equation [29].Using generalized linear regression, we computed geometric mean values and 95%confidence intervals (CIs) for hormone concentrations for the following genotypes: CYP17(A1/A1, A1/A2, A2/A2), CYP1B1 (Leu/Leu, Leu/Val, Val/Val), COMT (Val/Val, Val/Met,Met/Met), and SHBG (Asp/Asp, Asp/Asn and Asn/Asn). Hormone levels were entered intomodels as log-transformed variables due to deviations in the original values from the normaldistribution; final estimates were exponentiated. For CYP17, CYP1B1 and COMT, analyseswere performed separately for each genotype to compare hormone levels by heterozygousand homozygous variant genotypes to the homozygous wild-type (reference) using indicatorvariables. Due to the low frequency of the homozygous variant genotype for SHBG,heterozygous and homozygous variants were combined for comparison with thehomozygous wildtype. The androgenic hormones (total testosterone, free testosterone, andDHEAS) are presented for CYP17 and SHBG only because CYP1B1 and COMT act onestrogen alone [11]. Each model was assessed for the presence of non-linearity,heteroskedasticity, and possible outliers using normal quantile plots, as well as plots of thestudentized residuals versus X values and fitted values. Trend tests were performed byincluding the genotype in a linear model.

All genotypes were assessed for potential interaction with tamoxifen use at the time of theblood draw (yes, no), body mass index (BMI) (<30, ≥30) and race (non-Hispanic White,Hispanic White, Non-White); results are stratified when appropriate. In addition, thefollowing variables were considered a priori as possible confounders of the associationsbetween genotype and hormone levels: study site (Washington, California, New Mexico),age at diagnosis (continuous), BMI (continuous), percent body fat (continuous), currenttamoxifen use (yes, no), ever used hormone therapy (yes, no), ever used oral contraceptives(yes, no), number of ovaries remaining (0, 1+), stage at diagnosis (in situ, stage 1, stage 2),ER status (positive, negative, missing), progesterone receptor status (positive, negative,missing), current smoking status (yes, no), currently drink alcohol (yes, no), marital status(married, widowed, divorced, separated, never married), months since last breast cancertreatment (continuous), and additional polymorphisms that preceded the one in question inthe biosynthesis or metabolism pathway of estrogen. Final models were adjusted for thosevariables that were known a priori to be related to estrogen levels or those that changed the

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coefficient estimates by 10% or more: study site, race, tamoxifen use, number of remainingovaries, HT use, marital status, BMI, stage, age.

ResultsThis analysis included 202 non-Hispanic white, 33 Hispanic white, and 131 African-American breast cancer survivors. By study design, the distribution of study subjects byrace/ethnicity differed between study sites. Compared to non-Hispanic white women, theAfrican-American women were younger and less likely to drink alcohol or have usedtamoxifen and HT (Table 2). Further, a larger proportion of the African-American womenwere obese (BMI ≥ 30) or diagnosed with more advanced disease. Although slightlyyounger and less likely to use HT, the Hispanic white women were similar to the non-Hispanic whites with respect to baseline characteristics. The observed variant allelefrequencies differed by race/ethnicity for COMT (p=0.001), CYP1B1 (p<0.001) and SHBG(p=0.003). There was no meaningful racial/ethnic difference in the genotype distribution forCYP17 (p=0.89). Allele frequencies for all genes of interest were in Hardy-Weinbergequilibrium within each racial/ethnic group.

Table 3 shows the mean (geometric) serum hormone levels approximately 24 monthsfollowing diagnosis by race/ethnicity. Compared to non-Hispanic whites, Hispanic womenhad significantly lower total estrone (p <0.0001), total testosterone (p<0.0001) and freetestosterone (p=0.002); the opposite was found for African-American women who had thehighest levels for those hormones (estrone, p <0.0001; testosterone, p <0.0001; freetestosterone, p<0.0001) as well as SHBG (p=0.02). There were no differences by race/ethnicity for total estradiol, free estradiol, and DHEAS.

The associations between the CYP17 polymorphism and several hormones were modified byrace/ethnicity (Table 4). Because mean hormone levels did not differ for women with theA1/A2 heterozygous and A2/A2 homozygous variant genotypes, the two groups werecombined. Hispanic women with the variant genotype had androgen levels 46–87% higherthan those carrying the wildtype alleles. In contrast, androgen levels were 13–20% loweramong those with the variant type in non-Hispanic white individuals. Compared to thewildtype, non-Hispanic white women with the variant genotype had lower estrone whereas aslight increase was observed for African-American group (p for interaction = 0.03). AmongAfrican-American women, there were no meaningful differences in circulating hormonelevels by CYP17 genotype.

Race/ethnicity was not an important effect modifier for the remaining genes (data notshown). We found little association between serum estrone, estradiol, free estradiol, orSHBG and the CYP1B1 or COMT genotypes (data not shown). We observed an interactionbetween current tamoxifen use and the SHBG genotype for several of the hormones (Table5). Among women currently using tamoxifen, those with at least one variant allele of theSHBG polymorphism had mean serum SHBG and free testosterone concentrations that were78% higher and 39% lower, respectively, than those with the wildtype. In contrast, forwomen not using tamoxifen, there was no difference in serum SHBG or free testosteronelevels by SHBG genotype. However, free estradiol was elevated among women with thevariant compared to the wildtype SHBG genotype only among women not taking tamoxifen.

DiscussionWe found little evidence that polymorphisms for several genes involved with estrogen andandrogen metabolism (CYP17, CYP1B1, COMT or SHBG) were associated with serum sexhormone levels among a population of postmenopausal breast cancer survivors. However,

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we did observe associations for CYP17 and SHBG with Hispanic ethnicity and currenttamoxifen use, respectively. Non-Hispanic white women who were heterozygous orhomozygous for the variant allele of the CYP17 genotype had lower estrone, totaltestosterone, free testosterone, and DHEAS concentrations compared to womenhomozygous for the wildtype allele. This finding is contradictory to the hypothesized effectwhich predicted higher hormone levels for individuals with the variant genotype. AmongHispanic whites, the observed effect was in the expected direction with increased estroneand androgen concentrations noted for the variant allele.

Our results for CYP17 add to the growing number of studies reporting little or no associationfor genetic control by this particular SNP and hormone levels [18,19,30–36]. Similarly,there is little evidence that circulating hormone levels vary substantially by the CYP1B1 orCOMT genotypes [18,19,35,36]; however, the relationship with urinary metabolites ofestrogen has been more consistent with higher concentrations observed for the variantgenotypes [19,37]. One reason for the lack of an observed effect may be due to the limitedability of most previous studies to look at polymorphisms for several genes or SNPs jointly.For instance, it has been suggested that the functional relevance of CYP1B1 is dependent onother polymorphisms of the same gene [38]. Similarly, hormone metabolism is a complexbiological pathway and it is more likely that disruptions at multiple points alter hormonelevels.

Some [18,39], but not all [40], previous studies of the SHBG Asp327 Asn polymorphism inpostmenopausal healthy women have reported higher circulating SHBG levels in carriers ofthe Asn variant. In our study of breast cancer patients, this finding was restricted to womentaking tamoxifen at the time of the blood draw. Among the non-users of tamoxifen, wefound no difference in serum SHBG by genotype, but did observe a rise in free estradiolamong those with the variant allele which was not expected. The study by Haiman et al.which reported no association for the Asp327 Asn genotype alone, found lowered serumSHBG levels for women with the wildtype Asp genotype in combination with a repeatpolymorphism in the promoter of the SHBG gene. This suggests that the function of onepolymorphism may depend on the presence of others [40]. However, our subgroup findingsfor CYP17 and SHBG may also be due to chance given our small numbers and makingmultiple statistical comparisons [41].

One strength of this study is the inclusion of a multi-ethnic cohort of women with largenumbers of non-Hispanic white women and African-Americans. The allele frequencies ofmany genotypes differ by race or ethnicity and it is probable that particular alleles are linkedto other important polymorphisms among particular groups. To our knowledge, this is theonly study reporting associations between these specific genotypes and hormoneconcentrations among a population of breast cancer survivors. Because of the relationshipbetween breast cancer and estrogen, this is a population where estrogen levels are importantto study. It is possible that the relationship in patients is different compared to healthycontrols. In order to reduce the influence of treatment, hormone concentrations weremeasured approximately two years following diagnosis. Half of the women in this studywere currently taking tamoxifen which can alter estrogen levels. However, with theexception of the SHBG gene, we did not find meaningful genetic associations when bothtamoxifen users and non-users were investigated separately.

This study has several limitations. This study was too small to perform stratified analyses formultiple factors simultaneously. We were also unable to assess the joint effects of multiplegenes involved with the sex hormone metabolic pathways. We did not have measurementsof estrogen metabolites which may be more strongly influenced by COMT and CYP1B1genotypes. It is also possible that we did not measure the functionally relevant

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polymorphisms in the selected genes [8,42]. The coefficients of variation for the estrogenassay were fairly high, likely due to the difficulty of measuring estrogens at low levels inpostmenopausal women [20]. These high CVs may be one reason we did not observe strongassociations between the genotypes and estrogens.

In conclusion, this study offers little support that polymorphisms in genes involved with sexhormone metabolism directly determine levels of circulating hormones. To understand betterthe functional relevance of polymorphisms in hormone metabolism and potentialconsequences regarding risk of cancer and other hormone-dependent diseases, future studiesshould be large enough to evaluate the independent and joint effects of polymorphisms ingenes at each step of the sex hormone metabolic pathway. Future investigations shouldinclude both patients and healthy controls to understand whether the functional relevance ofthe genes under study is different in these two populations. Another issue to address instudies with breast cancer patients is the potential interaction between genotype and use ofaromatase inhibitors on sex hormones, since women with ER positive tumors will mostlikely be treated with these drugs in the future.

AcknowledgmentsThis study was supported through National Cancer Institute contracts N01-CN-75036-20, NO1-CN-05228, andNO1-PC-67010. Dr. Abrahamson was also supported by a National Cancer Institute training grant (R25 CA94880).

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33. Marszalek B, Lacinski M, Babych N, Capla E, Biernacka-Lukanty J, Warenik-Szymankiewicz A,Trzeciak WH. Investigations on the genetic polymorphism in the region of CYP17 gene encoding5'-UTR in patients with polycystic ovarian syndrome. Gynecol Endocrinol 2001;15(2):123–128.[PubMed: 11379008]

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Table 1

Primer and probe sequences used for genotyping of CYP17, CYP1B1, COMT and SHBG genes.

Gene Primer sequence Probe sequence

CYP17 Forward GGCCTCCTTGTGCCCTAGAGT Wild-type VIC-TACTCCACTGCTGTCTATCTTGCCTGCC-TAMRA

Reverse CCACGAGCTCCCACATGGT Variant 6FAM-TACTCCACCGCTGTCTATCTTGCCTGC-TAMRA

CYP1B1 Forward GCTACCACATTCCCAAGGACACT Wild-type VIC-TCATGACCCAGTGAAGTGGCCT-TAMRA

Reverse GTCCAAGAATCGAGCTGGATCA Variant 6FAM-TCATGACCCACTGAAGTGGCCT-TAMRA

COMT Forward GAGGCTCATCACCATCGAGATC Wild-type VIC-TGTCCTTCACGCCAAGCGAAATCC-TAMRA

Reverse GTCTGACAACGGGTCAGGCAT Variant 6FAM-TGTCCTTCATGCCAGCGAAATCCA-TAMRA

SHBG Forward CGAGCCACCTTAATGCTCTAATGCC Wild-type VIC-CCTCCCTCTAGGAGAAGACTCTTCCAC-TAMRA

Reverse CCAGCCTCTGACCTTGTGCCC Variant 6FAM-CCTCCCTCTAGGAGAAAACTCTTCCAC-TAMRA


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Table 2

Selected characteristics of 366a postmenopausal breast cancer survivors, stratified by race and ethnicity.

Non-HispanicWhite, n=202

N (%)

HispanicWhite, n=33

N (%)

African-American,n=131N (%)

P valueb

Age at diagnosis (years)

40–54 82 (41) 17 (51) 73 (56) 0.02

55–60 120 (59) 16 (49) 58 (44)

Site

Washington 77 (38) 2 (6) 1 (1) n/a

New Mexico 125 (62) 31 (94) 0 (0)

Southern California 0 (0) 0 (0) 130 (99)

Tamoxifen use at blood draw

No 96 (47) 14 (42) 75 (57) 0.14

Yes 106 (53) 19 (58) 56 (43)

Stage

In situ 40 (20) 5 (15) 31 (24) 0.002

Local 119 (59) 20 (61) 50 (38)

Regional 43 (21) 8 (24.) 50 (38)

Ovaries remaining

None 38 (19) 6 (18) 24 (18) 0.99

At least 1 164 (81) 27 (82) 106 (82)

Ever used HRT

Never 59 (29) 13 (39) 86 (66) <0.001

Ever 142 (71) 20 (61) 45 (34)

Body Mass Index, kg/m2

< 25 91 (45) 16 (48) 30 (23) <0.001

25–29.9 62 (31) 11 (33) 36 (27)

30+ 49 (24) 6 (18) 65 (50)

Marital Status

Married 134 (67) 22 (69) 50 (38) <0.001c

Widowed 15 (7) 5 (16) 22 (17)

Divorced/separated 40 (20) 4 (12) 50 (38)

Never married 12 (6) 1 (3) 9 (7)

Smoking Status

Never 95 (47) 17 (52) 61 (47) 0.75

Former 84 (42) 12 (36) 49 (37)

Current 23 (12) 4 (12) 21 (16)

Alcohol in last year

No 45 (22) 8 (24) 77 (59) <0.001

Yes 157 (78) 25 (76) 54 (41)

CYP17

A1/A1 (wild-type) 73 (36) 11 (33) 52 (40) 0.89


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Non-HispanicWhite, n=202

N (%)

HispanicWhite, n=33

N (%)

African-American,n=131N (%)

P valueb

A1/A2 102 (50) 16 (49) 61 (46)

A2/A2 27 (13) 6 (18) 18 (14)

CYP1B1

Val/Val (wild-type) 53 (26) 9 (27) 81 (62) <0.001

Val/Leu 111 (55) 11 (33) 42 (32)

Leu/Leu 38 (19) 13 (40) 8 (6)

COMT

Val/Val (wild-type) 51 (25) 12 (36) 55 (42) 0.001

Val/Met 92 (46) 13 (39) 61 (46)

Met/Met 59 (29) 8 (25) 15 (12)

SHBG gened

Asp/Asp (wild-type) 61 (79) n/a 123 (94) 0.003

Asp/Asn or Asn/Asn 16 (21) n/a 8 (6)

aA few women had missing values for several variables so all subgroups do not add to the total n for the specific racial/ethnic groups.

bχ2 test for differences in characteristics across race/ethnicity.

cFisher’s exact test used because of small cell sizes.

dThe SHBG polymorphism was measured not measured in the 156 women from New Mexico; 2 remaining non-Hispanic women from the other

sites were eliminated from analyses of the SHBG genotype.


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Table 3

Geometric means and 95% confidence intervals for serum hormone concentrations approximately 24 monthsfollowing a breast cancer diagnosis, stratified by race and ethnicity.

Non-Hispanic White,mean (95% CI)

Hispanic White,mean (95% CI)

African-American,mean (95% CI)

Estrone (pg/mL) 21.3 (19.6, 23.2) 16.4 (13.2, 20.3)a 31.4 (29.2, 33.8)a

Estradiol (pg/mL) 14.1 (12.6, 15.7) 13.5 (10.7–17.0) 14.0 (13.0, 15.2)

Free estradiol (pg/mL) 0.34 (0.30, 0.38) 0.30 (0.24–0.40) 0.31 (0.28, 0.34)

SHBG (nmol/L) 46.5 (43.1, 50.2) 51.3 (41.3, 63.7) 53.8 (49.4, 58.6)a

Testosterone (pg/mL) 172 (156, 190) 138 (102, 186)a 241 (217, 269)a

Free Testosterone (pg/mL) 3.12 (2.80, 3.47) 2.38 (1.70, 3.33)a 4.06 (3.61, 4.57)a

DHEAS (ug/dL) 58.2 (53.02, 63.8) 51.3 (37.4, 70.2) 65.01 (57.3, 73.8)

ap ≤ 0.05 using ANOVA, comparing mean hormone levels to non-Hispanic white women


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Table 4

Adjusteda geometric means of sex hormones by CYP17 genotype in postmenopausal breast cancer survivors,stratified by race and ethnicity.

A1/A1 A1/A2 and A2/A2

Geometric Mean(95% CI)


Interactionp-valueb

Non-Hispanic White

N 70 127

Estrone 21.6 (18.7, 24.8) 18.0 (15.5, 21.0)c

Estradiol 8.7 (7.3, 10.4) 8.5 (7.2, 10.1)

Free estradiol 0.23 (0.19 0.28) 0.23 (0.19, 0.27)

SHBG 31.4 (27.4, 36.0) 30.6 (26.9, 34.7)

Testosterone 240 (203, 283) 191 (164, 223)c

Free testosterone 5.3 (4.5, 6.2) 4.3 (3.7, 5.0)c

DHEAS 60.8 (51.4, 71.8) 52.6 (45.4, 60.9)d

Hispanic White

N 10 20

Estrone 14.6 (9.8, 21.7) 15.8 (11.8, 21.0) 0.31

Estradiol 9.8 (6.5, 14.7) 6.7 (5.1–8.9) 0.20

Free estradiol 0.25 (0.17–0.39) 0.19 (0.14–0.26) 0.31

SHBG 35.0 (27.9, 43.9) 27.4 (22.2, 33.8) 0.16

Testosterone 145 (84, 248) 240 (182, 314)c 0.02

Free testosterone 3.0 (1.7, 5.3) 5.6 (4.2, 7.5)c 0.01

DHEAS 43.7 (30.1, 63.4) 63.8 (46.5, 87.5)d 0.04

African-American

N 51 78

Estrone 35.1 (28.6, 43.0) 37.6 (32.1, 44.1) 0.03

Estradiol 34.1 (27.8, 41.8) 33.0 (28.0, 39.0) 0.97

Free estradiol 0.61 (0.49, 0.76) 0.58 (0.49, 0.69) 0.71

SHBG 107 (89, 131) 117 (102, 137) 0.23

Testosterone 160 (121, 214) 173 (142, 211) 0.05

Free testosterone 1.9 (1.4, 2.6) 2.0 (1.6, 2.4) 0.13

DHEAS 74.0 (56.2, 97.4) 64.9 (53.0, 79.3) 0.93

aAdjusted for study site, current tamoxifen use, number of remaining ovaries, ever used HRT, marital status, stage, age at diagnosis, and body mass

index.

bComparing mean hormone levels by genotype to non-Hispanic white women

cp ≤ 0.05, comparing mean hormone levels of the variant (A1/A2 or A2/A2) to the wildtype (A1/A1) genotype within each race/ethnicity group

dp ≤ 0.10, comparing mean hormone levels of the variant (A1/A2 or A2/A2) to the wildtype (A1/A1) genotype within each race/ethnicity group


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Table 5

Adjusteda geometric means of various sex hormones for the SHBG genotype in postmenopausal breast cancersurvivors, stratified by tamoxifen status.

Asp/Asp Asp/Asn or Asn/Asn

Geometric Mean (95%CI)


Interactionp-valueb

Not using tamoxifen

N 94 11

Estrone 27.3 (25.2, 29.6) 26.8 (22.1, 32.6)

Estradiol 11.1 (10.2, 12.1) 18.9 (14.9, 23.9)

Free estradiol 0.27 (0.25, 0.29) 0.46 (0.36, 0.59)c

SHBG 44.2 (41.0, 47.8) 46.8 (35.4, 61.9)

Testosterone 234 (213, 258) 227 (166, 313)

Free testosterone 4.4 (3.9, 4.8) 4.0 (2.9, 5.5)

DHEAS 64.8 (58.1, 72.3) 79.7 (56.0, 113.4)

Using tamoxifen

N 88 13

Estrone 29.6 (27.7, 31.6) 25.2 (18.0, 35.3) 0.41

Estradiol 13.3 (12.4, 14.3) 17.8 (13.3, 23.9) 0.10

Free estradiol 0.31 (0.29, 0.34) 0.35 (0.27, 0.45) 0.008

SHBG 50.8 (47.9, 53.8) 90.8 (77.5, 106.2)c 0.006

Testosterone 236 (219, 255) 195 (144, 262) 0.47

Free testosterone 4.1 (3.8, 4.5) 2.5 (1.9, 3.4)c 0.04

DHEAS 69.5 (63.2, 76.5) 59.5 (39.0, 90.7) 0.17

aAdjusted for study site, race, ovaries remaining, ever HRT use, marital status, stage, age at diagnosis, and BMI.

bComparing mean hormone levels by Tamoxifen use.

cp ≤ 0.05, comparing mean hormone levels for the variant (Asp/Asn or Asn/Asn) and the wildtype (Asp/Asp) genotype within each race/ethnicity

group.


associations between the cyp17, cypib1, comt and shbg polymorphisms and serum sex hormones in...

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